INFORM humanitarian risk panel by country
Country-year panel of the EU Joint Research Centre INFORM Risk Index (2026 release trend file): headline 0-10 humanitarian crisis/disaster risk plus its three 0-10 dimensions (hazard & exposure, vulnerability, lack of coping capacity) and six categories (natural/human hazard; socio-economic/vulnerable groups; institutional/infrastructure coping), 191 countries 2017-2026, with per-year ranks, year-on-year changes and 10-year risk-trend slopes. Keyless JRC download; joins on country_code with the catalog's other global panels. Fills the catalog's humanitarian crisis-risk gap (existing disaster coverage tracks realized impacts, not forward risk).
- Rows
- 1,910
- Columns
- 17
- Source cadence
- Yearly
- Last refreshed
- Oct 6, 2026
- Theme
- humanitarian
| Column | Type | Description |
|---|---|---|
| country_code | string | ISO 3166-1 alpha-3 country code (workbook column 'Iso3'). |
| country | string | Country name from the catalog's canonical ISO3 mapper. |
| year | integer | INFORM release year (workbook column 'INFORMYear', 2017-2026). |
| inform_risk | float | Headline INFORM Risk Index, 0-10 (10 = highest risk of a humanitarian crisis or disaster overwhelming national response capacity). Geometric mean of the three dimensions. (unit: index points) |
| hazard_exposure | float | Hazard & Exposure dimension, 0-10: probability of physical exposure to hazards (natural and human). (unit: score) |
| vulnerability | float | Vulnerability dimension, 0-10: intrinsic predisposition of the population to be affected (socio-economic and vulnerable groups). (unit: score) |
| coping_capacity_lack | float | Lack of Coping Capacity dimension, 0-10 (higher = lower capacity): institutional strength and infrastructure for coping and recovery. (unit: score) |
| hazard_natural | float | Natural hazard category, 0-10 (earthquake, tsunami, flood, cyclone, drought, epidemic components). (unit: score) |
| hazard_human | float | Human hazard category, 0-10 (current and projected conflict intensity). (unit: score) |
| vuln_socioeconomic | float | Socio-economic vulnerability category, 0-10 (development, inequality, aid dependency). (unit: score) |
| vuln_groups | float | Vulnerable groups category, 0-10 (uprooted people, health, food security, recent shocks). (unit: score) |
| coping_institutional | float | Institutional coping-capacity category, 0-10 (disaster risk reduction, governance). (unit: score) |
| coping_infrastructure | float | Infrastructure coping-capacity category, 0-10 (health care, communication, physical infrastructure). (unit: score) |
| inform_rank | float | Per-year cross-country rank on the headline index (1 = highest risk). (unit: rank) |
| inform_yoy_pp | float | Year-on-year change of the headline index in points (null for each country's first year). (unit: index points) |
| inform_trend_slope | float | OLS slope of the headline index over the country's available years (points per year; positive = worsening risk). (unit: index points/year) |
| row_hash | string | Deterministic 12-hex row identity hash (country_code|year). |
First 10 sample rows — a preview, not the complete dataset.
| country_code | country | year | inform_risk | hazard_exposure | vulnerability | coping_capacity_lack | hazard_natural | hazard_human | vuln_socioeconomic | vuln_groups | coping_institutional | coping_infrastructure | inform_rank | inform_yoy_pp | inform_trend_slope | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AFG | Afghanistan | 2,017 | 8 | 8.6 | 7.7 | 7.6 | 5.4 | 10 | 8.1 | 7.3 | 7.6 | 7.5 | 2 | — | -0.028 | 2fec81444326 |
| AFG | Afghanistan | 2,018 | 8 | 8.6 | 7.8 | 7.6 | 5.4 | 10 | 8.1 | 7.4 | 7.7 | 7.4 | 2 | 0 | -0.028 | 3d0b6d73d332 |
| AFG | Afghanistan | 2,019 | 8.2 | 8.6 | 8.4 | 7.5 | 5.6 | 10 | 8 | 8.7 | 7.7 | 7.2 | 2 | 0.2 | -0.028 | d299ae6d5cea |
| AFG | Afghanistan | 2,020 | 8.1 | 8.6 | 8.4 | 7.4 | 5.6 | 10 | 7.9 | 8.8 | 7.7 | 7.1 | 3 | -0.1 | -0.028 | 3d882afff5eb |
| AFG | Afghanistan | 2,021 | 8.1 | 8.6 | 8.3 | 7.4 | 5.5 | 10 | 7.9 | 8.6 | 7.7 | 7.1 | 3 | 0 | -0.028 | 564fc0ab1550 |
| AFG | Afghanistan | 2,022 | 8.2 | 8.6 | 8.4 | 7.5 | 5.6 | 10 | 7.8 | 8.9 | 7.8 | 7.1 | 3 | 0.1 | -0.028 | 4ef27c61ce52 |
| AFG | Afghanistan | 2,023 | 8.1 | 8.5 | 8.5 | 7.4 | 5.6 | 9.9 | 8 | 9 | 7.7 | 7 | 4 | -0.1 | -0.028 | 75248454bf04 |
| AFG | Afghanistan | 2,024 | 7.9 | 7.8 | 8.4 | 7.4 | 5.6 | 9.1 | 8.1 | 8.7 | 7.8 | 6.9 | 5 | -0.2 | -0.028 | a858340addf1 |
| AFG | Afghanistan | 2,025 | 7.8 | 7.6 | 8.3 | 7.4 | 5.6 | 8.9 | 8.1 | 8.4 | 7.9 | 6.9 | 7 | -0.1 | -0.028 | 31fc2b3933e8 |
| AFG | Afghanistan | 2,026 | 7.8 | 7.7 | 8.3 | 7.4 | 5.7 | 9 | 8 | 8.6 | 7.9 | 6.9 | 6 | 0 | -0.028 | 88624ef39073 |
- Current
20261006T042424Z-f52accc6a518 · sha256 f52accc6a518…
1,910 rows · first snapshot
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/inform_risk_intel/inform_risk_panel" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/inform_risk_intel/inform_risk_panel").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/inform_risk_intel/inform_risk_panel
Tip: fetch /llms.txt for the full machine-readable catalog.
Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.
Cite this snapshot
Pinned to snapshot 20261006T042424Z-f52accc6a518 and its content hash, so readers get exactly the data you used.
INFORM humanitarian risk intelligence. (2026). INFORM humanitarian risk panel by country [Data set, snapshot 20261006T042424Z-f52accc6a518, sha256 f52accc6a518]. Datazimuts. Retrieved 2026-10-06, from https://datazimuts.com/en/datasets/inform_risk_intel/inform_risk_panel?snapshot=20261006T042424Z-f52accc6a518
@misc{dz_inform_risk_intel_inform_risk_panel_f52accc6,
title = {{INFORM humanitarian risk panel by country}},
author = {{INFORM humanitarian risk intelligence}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/inform_risk_intel/inform_risk_panel?snapshot=20261006T042424Z-f52accc6a518}},
note = {Snapshot 20261006T042424Z-f52accc6a518, sha256 f52accc6a518cc6cf56d7137ef55a629a28ca86c200ab280b024d1a5e8e363a6; accessed 2026-10-06}
}Embed a table or a chart
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